We have implemented a controller of the self-tuning type to be used for the automated control of blood pressure in dogs. The self-tuning controller has properties which would seem to ideally suit it for physiological control. The controller is inherently stochastic, and is, therefore, usable in a noisy environment. As it is based on a minimal variance regulator, the controller is optimal in the minimal variance sense. Finally, the self-tuning controller is adaptive (through the use of on-line model estimation). The primary goal for the coming year is to evaluate the performance of the stochastic regulator in animal experiments. The performance of the self-tuning and non-self-tuning regulators will be compared with each other, and with that of a trained anesthesiologist. The models obtained by the self-tuning regulators will be compared with those obtained by bolus-injections.